3d

水印要求完全不被修改，完全脆弱水印一般是从空域LSB算法演变而来。(Watermark demands nothing to modify, the fragile watermark is completely general LSB algorithm has evolved the airspace。)

随着这些年计算机硬件水平的发展, 计算速度的提高, 源自序列蒙特卡罗方法的蒙特卡罗粒子滤波方法的应用研究又重新活跃起来,本()

这是我们非线性课程的一次作业，有分岔图，蛛网图，庞加莱截面，希望对大家有用。(This is our first non-linear operation of the curriculum, there is bifurcation diagram, spider diagram, Poincare section, in the hope that useful to everyone.)

在灰度图像中进行直线检测，带实验效果图像。利用快速Hough变换，能够正确查找线段端点。(In the gray image in a straight line detection, the experiment with the effect of the image. Using fast Hough transform, to correctly segment endpoint search.)

H264的VERILOG代码,基本实现了全部的功能(H264 of the Verilog code, the basic realization of all the functions)

说明：  Projection Metric Learning on Grassmann Manifold with Application to Video based Face Recognition

常规处理mt处理软件导出的数据文件，可以绘制出视电阻率和相位曲线，以及误差棒大小(The apparent resistivity and phase curves and the size of the error bar can be drawn by the conventional processing of data files derived from the MT processing software.)

说明：  据的规范化程序,消除数据的量纲对处理结果的影响,数据点之间距离的计算程序(According to the standardized program, the influence of the dimension of the data on the processing results is eliminated, and the calculation program of the distance between the data points is obtained.)

图像盲解卷积复原，一模方法，算法在压缩包内(Blind Image Deconvolution recovery, a model approach, the algorithm in the compressed package)

说明：  机器学习专门研究计算机怎样模拟或实现人类的学习行为，以获取新的知识或技 能，为包括人脸识别领域的人工智能的发展做出了极大的贡献。本文探索如何应用机器学习中的一些技术，使计算机更好地完成人脸识别领域中的人脸检测和人脸验证。 在人脸检测方面，针对如何快速、准确地检出人脸的问题，基于DLIB中特征模型，可以快速提取检测出人脸，并且提取出人脸特征点,主要作用就是快速检测定位人脸。在训练过程中，引入了ResNet机器学习算法，该算法采用多层卷积神经网络结构，对人脸进行多层特征提取和描述，得到人脸特征描述符。通过测试可以证实了上述方法能够检测和识别人脸。(In terms of face detection, for the problem of how to detect faces quickly and accurately, based on the feature model in DLIB, you can quickly extract and detect faces, and extract face feature points, the main role is to quickly detect and locate faces. In the training process, the VGG-FACE machine learning algorithm is introduced. This algorithm uses a multi-layer convolutional neural network structure to perform multi-layer feature extraction and description on the face to obtain the face feature descriptor. Tests can confirm that the above method can detect and recognize human faces.)